Finding the Faithless: Perceived Atheist Prevalence Reduces Anti-Atheist Prejudice
Bibliographic record
Abstract
Although prejudice is typically positively related to relative outgroup size, four studies found converging evidence that perceived atheist prevalence reduces anti-atheist prejudice. Study 1 demonstrated that anti-atheist prejudice among religious believers is reduced in countries in which atheists are especially prevalent. Study 2 demonstrated that perceived atheist prevalence is negatively associated with anti-atheist prejudice. Study 3 demonstrated a causal relationship: Reminders of atheist prevalence reduced explicit distrust of atheists. These results appeared distinct from intergroup contact effects. Study 4 demonstrated that prevalence information decreased implicit atheist distrust. The latter two experiments provide the first evidence that mere prevalence information can reduce prejudice against any outgroup. These findings offer insights about anti-atheist prejudice, a poorly understood phenomenon. Furthermore, they suggest both novel directions for future prejudice research and potential interventions that could reduce a variety of prejudices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".